Founding support hire and de facto CX Lead. I design the systems, deploy the AI, own the vendor relationships, build the team, and make the commercial case. Support as an asset, not a cost centre.
At Series B and beyond, support stops being a helpdesk and starts being a retention mechanism. A broken customer experience at this stage doesn't just generate complaints. It puts ARR at risk. I understand that, and I build accordingly.
I joined Risk Ledger in March 2022 as their first and only support hire, with nothing in place. With 8+ years building support functions across SaaS, cybersecurity, government, and enterprise, I've spent the past four years operating as the de facto CX Lead, owning the function end-to-end: tooling budget, vendor procurement, team structure, SLA design, and board-facing capacity planning.
I've designed the hiring process for the team lead role above me, shaped the remit of every colleague in the function, and authored a five-year capacity plan with ARR-at-risk modelling tied directly to headcount and tooling investment. I think like an operator, not a support agent.
Based in London, UK, working across SaaS, cybersecurity, government, and enterprise environments.
I've built a support function from a blank canvas: no tooling, no processes, no team. I know what order things need to happen in, what to prioritise when everything feels urgent, and how to make enterprise customers feel looked after before the infrastructure exists to do it properly.
I've modelled ARR-at-risk, quantified churn prevention value, and written the 5-year capacity plan that ties support headcount directly to growth targets. I speak the language of founders and finance leads, not just support metrics. Every investment I've asked for has been backed by evidence.
540% ticket growth. One additional hire. That's not luck. It's deliberate investment in automation, AI, and self-serve infrastructure. I know how to build lean and still deliver enterprise-grade CSAT. When it is time to hire, I've already designed the process, written the job spec, and built the interview framework.
Every ticket is a signal. I build the reporting infrastructure to capture it, the frameworks to interpret it, and the relationships with Product and Engineering to act on it. At companies I've worked with, support data has directly shaped product roadmaps and commercial strategy — not just sat in a dashboard.
Operating as the de facto CX Lead — owning the full support function, its tooling budget, vendor relationships, and strategic direction through a period of 541% ticket volume growth. Maintaining 95%+ CSAT while building infrastructure for 10k+ annual tickets.
First and only support hire. Built the entire function from zero: no tooling, no processes, no team, no Help Centre. Took full ownership of budget decisions, vendor selection, tooling procurement, and the commercial case for every investment made.
Owned IT support operations across multiple high-security prison estates, supporting 2,000+ staff and 3,000+ residents in zero-tolerance environments where failure had immediate safety implications.
Senior escalation point within a high-volume, time-critical support operation for nationwide fulfilment. Developed the pattern recognition and cross-functional influence that would later define how I approach support operations at scale, identifying systemic failure points and working with Operations and Technology to fix them at source.
Handled complex, high-impact customer cases within a regulated insurance environment. Operated under strict audit and compliance requirements, building the discipline around documentation, process rigour, and stakeholder accountability that underpins how I run support operations today.
Designed, trained, and deployed Intercom's Fin AI agent with strict audience targeting. Batch tested against historical data, iterated on help article quality, then expanded. No set-and-forget: built full QA monitoring framework around it.
86.8% deflection · >90% CSAT · Significant annual cost savingBuilt a keyword and phrase-based automation framework in Intercom that automatically tags, routes, and responds to incoming conversations. Designed the full tag taxonomy from real data, forming the foundation for every reporting and trend analysis initiative.
30% reduction in manual first-touch · Foundation for all reportingIdentified the highest-volume repetitive ticket category, built keyword-triggered automation for immediate structured responses, and simultaneously used the ticket data to construct a cross-functional business case for a product-level fix that would reduce volume at source.
Automation as quick win · Product fix as long-term solveBuilt a reporting stack using custom Intercom reports and AI-assisted trend analysis to track CSAT, first response time, AI resolution rate, reopen rate, and survey response rates. Monthly insights delivered to CS and Product via Notion and Slack. Quarterly strategic findings presented to the wider business. Support as intelligence, not overhead.
Monthly + quarterly reporting cadence · Data-driven product decisionsLed end-to-end data residency migration coordinating across Engineering, IT, and Support. Zero downtime. Validated email deliverability, updated 75+ Help Centre links, branding, and social links. Negotiated a significant discount on contract renewal.
Zero downtime · 20% cost saving · GDPR compliantIndependently identified, evaluated, and piloted Synthesia for the Help Centre. Ran full security and TPRM assessments, tested 7+ languages, created a branded avatar, and secured executive budget approval with a meaningful enterprise discount.
Days → minutes for video content · Extends to Marketing & CSDesigned a tiered priority framework with internal service objectives held to a higher standard than contractual minimums. Built a 5-dimension QA scorecard (Accuracy, Completeness, Tone, Efficiency, Documentation) and piloted native SLA tracking in Intercom.
Tiered priority framework · 5-dimension QA scorecard · Native Intercom trackingAuthored a 5-year financially modelled roadmap covering hiring, team structure, US expansion, tooling costs, and ROI analysis. Includes ARR-at-risk modelling, churn prevention value, and an explicit growth case tying support investment to the company's next stage of scale.
5-year model · ARR-at-risk analysis · Growth-stage planningEmail was 56% of conversations but had zero CSAT coverage. Overall response rate was just 4%. Redesigned and extended the CSAT workflow with guardrails to exclude AI-only or closed-without-reply conversations. Response rate increased from 4% to 20.6%.
4% → 20.6% response rate · 56% channel gap closedIf you're scaling a support or CX function and want to talk through what that looks like in practice, I'm always happy to have the conversation.
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